Systems and methods for determining likelihood of traffic incident information

ABSTRACT

A method includes receiving a first set of images from an image capture device of a vehicle. The method also includes performing a first analysis of movement of biomechanical points of occupants of the vehicle in the first set of images. The method further includes receiving an indication that a traffic incident has occurred. The method also includes receiving a second set of images from the image capture device corresponding to when the traffic incident occurred. The method further includes performing a second analysis of movement of the biomechanical points of the occupants in the second set of images. The method also includes determining a likelihood of injury or a severity of injury to the occupants based on the first analysis of movement and the second analysis of movement.

CROSS REFERENCE TO RELATED APPLICATION

This application claims priority to and benefit from U.S. ProvisionalApplication No. 62/415,115 filed Oct. 31, 2016, and incorporates theentirety of the same by reference herein.

BACKGROUND

The present disclosure relates generally to traffic incidents, and moreparticularly to systems and methods for determining a likelihood and/ora severity of the traffic incidents by using an image capture device.

This section is intended to introduce the reader to various aspects ofart that may be related to various aspects of the present disclosure,which are described and/or claimed below. This discussion is believed tohelp provide the reader with background information to facilitate abetter understanding of the various aspects of the present disclosure.Accordingly, it is understood that these statements are to be read inthis light, and not as admissions of prior art.

With the advent of lower cost, more accessible image capture devices(e.g., vehicle-mounted cameras, smartphones, and the like) andwidespread communication networks (e.g., mobile networks, the Internet,and the like), capturing image data and communicating information basedon the image data when operating a vehicle is easier than ever. If thevehicle is involved in a traffic incident, capturing images related tothe traffic incident data may be particularly useful to emergencyservices, insurance companies, law enforcement agencies, and the like.

SUMMARY

In one embodiment, a data acquisition system for use in a vehicleincludes an image capture device, a communication interface, and, acontroller. The controller is communicatively coupled to the imagecapture device and communicatively coupled to the communicationinterface. The controller includes processors that receive a first setof images from the image capture device. The processors also identifybiomechanical points of occupants in the vehicle in the first set ofimages. The processors further perform a first analysis of movement ofthe biomechanical points of the occupants in the first set of images.The processors also receive an indication that a traffic incident hasoccurred. The processors further receive a second set of images from theimage capture device corresponding to when the traffic incidentoccurred. The processors also identify the biomechanical points of theoccupants in the vehicle in the second set of images. The processorsfurther perform a second analysis of movement of the biomechanicalpoints of the occupants in the second set of images. The processors alsodetermine a likelihood of injury or a severity of injury to theoccupants based on the first analysis of movement and the secondanalysis of movement. The processors further send an alert, via thecommunication interface, based on the likelihood or the severity ofinjury to the occupants.

In another embodiment, a method includes receiving a first set of imagesfrom an image capture device of a vehicle. The method also includesperforming a first analysis of movement of biomechanical points ofoccupants of the vehicle in the first set of images. The method furtherincludes receiving an indication that a traffic incident has occurred.The method also includes receiving a second set of images from the imagecapture device corresponding to when the traffic incident occurred. Themethod further includes performing a second analysis of movement of thebiomechanical points of the occupants in the second set of images. Themethod also includes determining a likelihood of injury or a severity ofinjury to the occupants based on the first analysis of movement and thesecond analysis of movement.

In yet another embodiment, tangible, non-transitory, machine-readablemedia include instructions that cause processors to perform a firstanalysis of movement of biomechanical points of occupants of a vehiclein a first set of images. The instructions also cause the processors toperform a second analysis of movement of the biomechanical points of theoccupants in a second set of images. The instructions further cause theprocessors to determine a likelihood of injury or a severity of injuryto the occupants based on the first analysis of movement and the secondanalysis of movement. The instructions also cause the processors to sendan instruction to alert an emergency service, an insurance company, or alaw enforcement agency, via the communication interface, based on thelikelihood or the severity of injury to the occupants.

BRIEF DESCRIPTION OF THE DRAWINGS

Various aspects of this disclosure may be better understood upon readingthe following detailed description and upon reference to the drawings inwhich:

FIG. 1 is a perspective view of a vehicle that includes a dataacquisition system in accordance with an embodiment of the presentdisclosure;

FIG. 2 is a first perspective view of the data acquisition system ofFIG. 1 as viewed from inside the vehicle, in accordance with anembodiment of the present disclosure;

FIG. 3 is a second perspective view of the data acquisition system ofFIG. 1 as viewed from the front of the vehicle, in accordance with anembodiment of the present disclosure;

FIG. 4 is a block diagram of the data acquisition system of FIG. 1, inaccordance with an embodiment of the present disclosure; and

FIG. 5 is a flowchart illustrating a method for determining a likelihoodof a traffic incident and/or a severity of the traffic incident, inaccordance with an embodiment of the present disclosure.

DETAILED DESCRIPTION OF SPECIFIC EMBODIMENTS

One or more specific embodiments will be described below. In an effortto provide a concise description of these embodiments, not all featuresof an actual implementation are described in the specification. Itshould be appreciated that in the development of any such actualimplementation, as in any engineering or design project, numerousimplementation-specific decisions must be made to achieve thedevelopers' specific goals, such as compliance with system-related andbusiness-related constraints, which may vary from one implementation toanother. Moreover, it should be appreciated that such a developmenteffort might be complex and time consuming, but would nevertheless be aroutine undertaking of design, fabrication, and manufacture for those ofordinary skill having the benefit of this disclosure.

The present disclosure relates generally to traffic incidents, and moreparticularly to systems and methods for determining a likelihood and/ora severity of the traffic incident by using an image capture device. Adata acquisition system may include the image capture device, which maybe a vehicle-mounted camera (e.g., dashboard camera or action camera),an electronic device (e.g., a smartphone or laptop) that may be separatefrom a vehicle that includes an image capture device (e.g., anintegrated camera), and the like. A controller of the data acquisitionsystem may analyze movement of biomechanical points of one or moreoccupants of a vehicle in sets of images provided by the image capturedevice before, during, and/or after the traffic incident. The controllermay also receive vehicle movement information (e.g., speed of thevehicle) from one or more sensors of the vehicle. The controller maythen determine the likelihood and/or the severity of injury to the oneor more occupants based on the analysis and/or the vehicle movementinformation. The controller may then send an instruction to alert anemergency service and/or an insurance company based on the likelihoodand/or the severity of injury to the one or more occupants.

With the foregoing in mind, FIG. 1 is a perspective view of a vehicle 10that includes a data acquisition system 12 in accordance with anembodiment of the present disclosure. While the vehicle 10 isillustrated as an automobile, it should be understood that the presentdisclosure applies to any suitable vehicle, such as a truck, motorcycle,commercial vehicle, recreational vehicle, all-terrain vehicle, boat,airplane, snowmobile, and the like. As illustrated, the data acquisitionsystem 12 is mounted to the vehicle 10 via a rearview mirror 14 of thevehicle 10. In some embodiments, the data acquisition system 12 orcomponents of the data acquisition system 12 may be mounted any suitableportion of the vehicle 10. For example, an image capture device of thedata acquisition system 12 may include a dashboard camera 16. It shouldbe noted that an image capture device includes any suitable device thatcaptures images, including, for example, a video capture device. In someembodiments, the data acquisition system 12 or components of the dataacquisition system 12 may be mounted to the exterior of the vehicle 10or separate from the vehicle 10. For example, a controller,communication interface, sensor, and/or the image capture device of thedata acquisition system 12 may be part of any suitable computing devicein the vehicle 10, such as a mobile electronic device of an occupant ofthe vehicle 10, including, and without limitation, a smartphone, laptop,wearable device, and the like.

FIG. 2 is a first perspective view of a data acquisition system 12 ofFIG. 1 as viewed from inside the vehicle 10, in accordance with anembodiment of the present disclosure. As illustrated, the dataacquisition system 12 is integrated in the rearview mirror 14 of thevehicle 10. In some embodiments, the data acquisition system 12 mayreplace the rearview mirror 14. The data acquisition system 12 includesa rear-facing image capture device 18. The image capture device 18 mayfunction at any suitable frame rate, including any frame rate between 20and 100 frames per second (fps), such as 23.976 fps, 23.98 fps, 24 fps,25 fps, 29.97 fps, 30 fps, 50 fps, 59.94 fps, 60 fps, and the like. Asillustrated, the data acquisition system 12 also includes a visualdisplay 20 that may provide a video feed of the images captured by theimage capture device 18.

FIG. 3 is a second perspective view of the data acquisition system 12 ofFIG. 1 as viewed from the front of the vehicle 10, in accordance with anembodiment of the present disclosure. As illustrated, the dataacquisition system 12 includes a housing 22 that may house components ofthe data acquisition system 12, such as a controller, a communicationsinterface, and the like. The data acquisition system 12 may include afront-facing image capture device 24 that may be used to capture imagesof other vehicles, road conditions, weather conditions, traffic signalsand signs, and other information that may relate to operating thevehicle 10.

FIG. 4 is a block diagram of the data acquisition system 12 of FIG. 1,in accordance with an embodiment of the present disclosure. The dataacquisition system 12 includes a controller 30 that includes one or moreprocessors 32 and one or more memory devices 34. The one or moreprocessors 32 (e.g., microprocessors) may execute software programsand/or instructions to determine a likelihood and/or a severity ofinjury to one or more occupants of the vehicle 10, contents of thevehicle 10, or aspects of the vehicle 10 itself. Moreover, the one ormore processors 32 may include multiple microprocessors, one or more“general-purpose” microprocessors, one or more special-purposemicroprocessors, and/or one or more application specific integratedcircuits (ASICS), or some combination thereof. For example, the one ormore processors 32 may include one or more reduced instruction set(RISC) processors. The one or more memory devices 34 may storeinformation such as control software, look up tables, configurationdata, etc. In some embodiments, the one or more processors 32 and/or theone or more memory devices 34 may be external to the controller 18. Theone or more memory devices 34 may include a tangible, non-transitory,machine-readable-medium, such as a volatile memory (e.g., a randomaccess memory (RAM)) and/or a nonvolatile memory (e.g., a read-onlymemory (ROM)). The one or more memory devices 34 may store a variety ofinformation and may be used for various purposes. For example, the oneor more memory devices 34 may store machine-readable and/orprocessor-executable instructions (e.g., firmware or software) for theone or more processors 32 to execute, such as instructions fordetermining the likelihood and/or the severity of injury to one or moreoccupants of the vehicle 10. The one or more memory devices 34 mayinclude one or more storage devices (e.g., nonvolatile storage devices)that may include read-only memory (ROM), flash memory, a hard drive, orany other suitable optical, magnetic, or solid-state storage medium, ora combination thereof.

As illustrated, the image capture device 18 is communicatively coupledto the controller 30. As such, images (or videos) captured by the imagecapture device 18 may be sent to the controller 30 for storage (e.g., inthe one or more memory devices 34), analysis (e.g., by the one or moreprocessors 32), forwarding (e.g., via one or more communicationinterfaces 36), or any other suitable purpose.

One or more sensors 38 may also be communicatively coupled to thecontroller 30. The one or more sensors 38 may sense information relatedto operating the vehicle 10. For example, the one or more sensors 38 mayinclude a vehicle speed sensor, a vehicle acceleration sensor, a vehiclelocation sensor, a vehicle wheel speed sensor, and/or any other suitablesensor related to operating the vehicle 10. As illustrated, in someembodiments, the one or more sensors 38 may be communicatively coupledto the controller 30 via the one or more communication interfaces 36.For example, a vehicle sensor 38 of the vehicle 10 may becommunicatively coupled to a vehicle bus (e.g., controller area network(CAN) bus) of the vehicle 10, which may communicate with the one or morecommunication interfaces 36, which is communicatively coupled to thecontroller 30. In this manner, the controller 30 may receive informationfrom the vehicle sensor 38 of the vehicle 10.

The data acquisition system 12 also includes the one or morecommunication interfaces 36. The one or more communication interfaces 36may enable the controller 30 to communicate with any suitablecommunication network 40. For example, as discussed above, acommunication interface 36 may enable the controller 30 to communicatewith a vehicle bus of the vehicle 10. The one or more communicationinterfaces 36 may also enable the data acquisition system 12 tocommunicate with additional communication networks 40. For example, acommunication interface 36 may enable the controller 30 to communicatewith wireless networks (e.g., mobile, WiFi, LAN, WAN, Internet, and thelike). In this manner, the one or more communication interfaces 36 mayenable the controller 30 to communicate with computing devices 42 ofemergency services, insurance companies, law enforcement agencies, andthe like, to provide alerts related to the likelihood and/or theseverity of injury to one or more occupants of the vehicle 10.

In some embodiments, the data acquisition system 12 may not be containedin a single electronic device, but may be components of multipleelectronic devices. For example, the image capture device 18 may be adashboard-mounted video camera, the one or more sensors 38 may be partof the vehicle 10, and the controller 30 and the communication interface36 may be part of a smartphone that belongs to an occupant of thevehicle 10. The controller 30 may communicate with the image capturedevice 18 and the one or more sensors 38 via the communication interface36 of the smartphone and communication interfaces 36 of the imagecapture device 18 and the vehicle 10.

FIG. 5 is a flowchart illustrating a method 50 for determining alikelihood and/or a severity of a traffic incident injury, in accordancewith an embodiment of the present disclosure. The method 50 may beperformed by any suitable device that may control components of the dataacquisition system 12, such as the controller 30. While the method 50 isdescribed using steps in a specific sequence, it should be understoodthat the present disclosure contemplates that the described steps may beperformed in different sequences than the sequence illustrated, andcertain described steps may be skipped or not performed altogether. Insome embodiments, the method 50 may be implemented by executinginstructions stored in a tangible, non-transitory, computer-readablemedium, such as the one or more memory devices 34, using a processor,such as the one or more processors 32.

As illustrated, the controller 30 receives (block 52) a first set ofimages from the image capture device 18 of the vehicle 10 (e.g.,obtained over a range of time). For example, the first set of images maybe a continuous set of images or frames (e.g., from a video capture) ofthe interior of the vehicle 10. The first set of images may also becaptured before a traffic incident has occurred.

The controller 30 identifies (block 54) one or more occupants in thefirst set of images. The one or more memory devices 34 may includesoftware that enables the controller 30 to identify the one or moreoccupants in the first set of images based on, for example, imagerecognition techniques. For example, artificial intelligence may utilizeimagery obtained from one or more perspectives to identify human forms(e.g., body shapes, features, faces) based on machine learningalgorithms.

The controller 30 identifies (block 56) multiple biomechanical points ofeach occupant of the one or more occupants identified in the first setof images. The biomechanical points may include eyes, shoulders, elbows,sternum, hips, knees, and/or center of mass, of the one or moreoccupants. The one or more memory devices 34 may include software thatenables the controller 30 to identify the multiple biomechanical pointsof each occupant of the one or more occupants in the first set of imagesbased on, for example, image recognition techniques. Such techniques mayemploy different points of view (e.g., stereo-imagery).

The controller 30 performs (block 58) a first analysis of movement ofthe multiple biomechanical points of each occupant of the one or moreoccupants identified in the first set of images. In particular, thecontroller 30 may, for each occupant, perform the first analysis bydetermining, mapping, and/or recognizing movement of each biomechanicalpoint to one or more other biomechanical points from a previous image toa next image for multiple images of the first set of images. In someembodiments, each biomechanical point may be tracked in threedimensional space for each occupant. The first analysis may includedetermining or calculating distance difference, speed, acceleration,and/or force between biomechanical points from a previous image to anext image. This may provide control cases for biomechanical movementfor each occupant of the one or more occupants in the vehicle 10. Insome embodiments, the controller 30 may repeatedly, continuously,periodically, or occasionally perform more analyses of movement duringoperation of the vehicle 10. The first analysis may be useful indetermining the likelihood and/or the severity of injury to the one ormore occupants of the vehicle 10.

The controller 30 receives (block 60) an indication that a trafficincident has occurred (e.g., in a range of time). The indication may bereceived via any suitable source. For example, the indication may besent from the one or more sensors 38 of the vehicle 10, such as anairbag deployment sensor, a crash indication sensor, a bumper proximitysensor, and the like. In some embodiments, the one or more memory device34 may include software configured to recognize that a traffic incidentoccurred based on analyzing images captured by the image capture device18. Indeed, the indication may also be based on detected movement ofvehicle occupants. In other embodiments, the indication may becommunicated to the controller 30 via the communication interface 36from an external source or vehicle component (e.g., sent by an emergencyservice or vehicle monitoring service).

The controller 30 receives (block 62) a second set of images (e.g.,obtained over a range of time) from the image capture device 18corresponding to when the traffic incident occurred. The controller 30then identifies (block 64) the one or more occupants in the second setof images and identifies (block 66) the multiple biomechanical points ofeach occupant of the one or more occupants in the second set of images.

The controller 30 performs (block 68) a second analysis of movement ofthe multiple biomechanical points of each occupant in the second set ofimages. Again, the controller 30 may, for each occupant, perform thesecond analysis by determining, mapping, and/or recognizing movement ofeach biomechanical point to one or more other biomechanical points froma previous image to a next image for multiple images of the second setof images. The second analysis may include determining or calculating atotal distance difference, speed, acceleration, and/or force betweenbiomechanical points from a previous image to a next image. The secondanalysis may be useful in determining the likelihood and/or the severityof injury to the one or more occupants of the vehicle 10.

The controller 30 receives (block 70) vehicle movement information fromthe one or more sensors 38 corresponding to when the traffic incidentoccurred. In particular, the vehicle movement information may be relatedto the speed and/or acceleration of the vehicle 10 when the trafficincident occurred. The vehicle movement information may be useful indetermining the likelihood and/or the severity of injury to the one ormore occupants of the vehicle 10.

The controller 30 determines (block 72) the likelihood and/or theseverity of injury to each occupant of the one or more occupants of thevehicle 10 based at least in part on the first analysis, the secondanalysis, and/or the vehicle movement information. In particular, theone or more memory devices 34 may include software and/or algorithms fordetermining the force that each occupant and each occupant'sbiomechanical points were subjected to based on inputs related to thefirst analysis, the second analysis, and/or the vehicle movementinformation. In some embodiments, the controller 30 may be able toconfirm or refine the determination of the likelihood and/or theseverity of injury to each occupant by analyzing a third set of imagesfrom the image capture device 18 corresponding to immediately after thetraffic incident occurred. Present embodiments may also capture andanalyze imagery associated with vehicle contents (e.g., loose objects inthe vehicle 10) and features (e.g., seats) to determine a likelihoodand/or severity of injury to occupants and/or the vehicle 10.

The controller 30 reports or sends (block 74) an alert or an instructionto alert an emergency service and/or an insurance company based at leastin part on the determined likelihood and/or the severity of injury toeach occupant of the one or more occupants of the vehicle 10. In someembodiments, additional or alternative entities may be alerted based atleast in part on the determined likelihood and/or the severity ofinjury, such as law enforcement agencies, fire departments, hospitals,and the like. For example, the controller 30 may transmit images (e.g.,at least a previous image and a next image) associated with the trafficincident, estimates of biomechanical forces for the one or moreoccupants, and/or the likelihood and/or severity of injury for the oneor more occupants to a central server of a law enforcement agency, firedepartment, hospital, and the like. In this manner, life-savingassistance and insurance-related services may be provided to thoseaffected by traffic incidents more quickly and efficiently in anautomated fashion.

While the embodiments set forth in the present disclosure may besusceptible to various modifications and alternative forms, specificembodiments have been shown by way of example in the drawings and havebeen described in detail herein. However, it should be understood thatthe disclosure is not intended to be limited to the particular formsdisclosed. The disclosure is to cover all modifications, equivalents,and alternatives falling within the spirit and scope of the disclosureas defined by the following appended claims.

What is claimed is:
 1. A data acquisition system for use in a vehiclecomprising: an image capture device; a communication interface; and acontroller communicatively coupled to the image capture device andcommunicatively coupled to the communication interface, wherein thecontroller comprises one or more processors configured to: receive afirst plurality of images from the image capture device; identify aplurality of biomechanical points of one or more occupants in thevehicle in the first plurality of images; perform a first analysis ofmovement of the plurality of the biomechanical points of the one or moreoccupants in the first plurality of images by determining movementbetween the plurality of biomechanical points of the one or moreoccupants in a first image of the first plurality of images and theplurality of biomechanical points of the one or more occupants in asecond image of the first plurality of images; receive an indicationthat a traffic incident has occurred; receive a second plurality ofimages from the image capture device corresponding to when the trafficincident occurred; identify the plurality of biomechanical points of theone or more occupants in the vehicle in the second plurality of images;perform a second analysis of movement of the plurality of thebiomechanical points of the one or more occupants in the secondplurality of images by determining movement between the plurality ofbiomechanical points of the one or more occupants in a first image ofthe second plurality of images and the plurality of biomechanical pointsof the one or more occupants in a second image of the second pluralityof images; determine a likelihood of injury, a severity of injury, or acombination thereof, to the one or more occupants based at least in parton the first analysis of movement and the second analysis of movement;and send an alert, via the communication interface, based at least inpart on the likelihood or the severity of injury to the one or moreoccupants.
 2. The data acquisition system of claim 1, comprising one ormore vehicle sensors, wherein the controller is communicatively coupledto the one or more vehicle sensors, wherein the controller is configuredto receive vehicle movement information from the one or more vehiclesensors corresponding to when the traffic incident occurred.
 3. The dataacquisition system of claim 2, wherein the one or more processors areconfigured to determine the likelihood of injury, the severity ofinjury, or a combination thereof, to the one or more occupants based atleast in part on the first analysis of movement, the second analysis ofmovement, and the vehicle movement information.
 4. The data acquisitionsystem of claim 2, wherein the controller is communicatively coupled tothe one or more vehicle sensors via the communication interface.
 5. Thedata acquisition system of claim 1, wherein the image capture devicecomprises the controller.
 6. The data acquisition system of claim 1,wherein a mobile electronic device of an occupant of the one or moreoccupants of the vehicle comprises the controller.
 7. A methodcomprising: receiving, via one or more processors, a first plurality ofimages from an image capture device of a vehicle; performing, via theone or more processors, a first analysis of movement of a plurality ofbiomechanical points of one or more occupants of the vehicle in thefirst plurality of images by determining movement of the plurality ofbiomechanical points of the one or more occupants between a first imageof the first plurality of images and a second image of the firstplurality of images; receiving, via the one or more processors, anindication that a traffic incident has occurred; receiving, via the oneor more processors, a second plurality of images from the image capturedevice corresponding to when the traffic incident occurred; performing,via the one or more processors, a second analysis of movement of theplurality of the biomechanical points of the one or more occupants inthe second plurality of images by determining movement of the pluralityof biomechanical points of the one or more occupants between a firstimage of the second plurality of images and a second image of the secondplurality of images; and determining and reporting, via the one or moreprocessors, a likelihood of injury, a severity of injury, or acombination thereof, to the one or more occupants based at least in parton the first analysis of movement and the second analysis of movement.8. The method of claim 7, comprising receiving, via the one or moreprocessors, a third plurality of images from the image capture devicecorresponding to after the traffic incident occurred.
 9. The method ofclaim 8, comprising performing, via the one or more processors, a thirdanalysis of movement of the plurality of the biomechanical points of theone or more occupants in the third plurality of images.
 10. The methodof claim 9, comprising refining or confirming, via the one or moreprocessors, the likelihood of injury, the severity of injury, or acombination thereof, to the one or more occupants based at least in parton the third analysis of movement.
 11. The method of claim 7,comprising: identifying, via the one or more processors, the one or moreoccupants in the first plurality of images; and identifying, via the oneor more processors, the one or more occupants in the second plurality ofimages.
 12. The method of claim 7, comprising: identifying, via the oneor more processors, the plurality of biomechanical points of the one ormore occupants in the first plurality of images; and identifying, viathe one or more processors, the plurality of biomechanical points of theone or more occupants in the second plurality of images.
 13. The methodof claim 7, comprising sending, via the one or more processors, aninstruction to alert an emergency service, an insurance company, a lawenforcement agency, or any combination thereof, via a communicationinterface, based at least in part on the likelihood or the severity ofinjury to the one or more occupants.
 14. The method of claim 8, whereinthe third plurality of images comprises captured imagery of vehiclecontents or features, wherein the method comprises analyzing, via theone or more processors, the captured imagery of vehicle contents orfeatures, and determining the likelihood of injury, the severity ofinjury, or the combination thereof, based at least in part on analyzingthe captured imagery of vehicle contents or features.
 15. The method ofclaim 7, wherein: the first analysis of movement comprises determiningor calculating distance difference, speed, acceleration, force, or acombination thereof, between the plurality of biomechanical points ofthe one or more occupants in the first image of the first plurality ofimages and the plurality of biomechanical points of the one or moreoccupants in the second image of the first plurality of images, or thesecond analysis of movement comprises determining or calculatingdistance difference, speed, acceleration, force, or a combinationthereof, between the plurality of biomechanical points of the one ormore occupants in the first image of the second plurality of images tothe plurality of biomechanical points of the one or more occupants inthe second image of the second plurality of images.
 16. One or moretangible, non-transitory, machine-readable media comprising instructionsconfigured to cause one or more processors to: perform a first analysisof movement of a plurality of biomechanical points of one or moreoccupants of a vehicle in a first plurality of images by recognizingmovement of the plurality of biomechanical points of the one or moreoccupants between a first image of the first plurality of images and asecond image of the first plurality of images; perform a second analysisof movement of the plurality of the biomechanical points of the one ormore occupants in a second plurality of images by recognizing movementof the plurality of biomechanical points of the one or more occupantsbetween a first image of the second plurality of images and a secondimage of the second plurality of images; determine a likelihood ofinjury, a severity of injury, or a combination thereof, to the one ormore occupants based at least in part on the first analysis of movementand the second analysis of movement; and send an instruction to alert anemergency service, an insurance company, a law enforcement agency, orany combination thereof, via a communication interface, based at leastin part on the likelihood or the severity of injury to the one or moreoccupants.
 17. The one or more machine-readable media of claim 16,comprising instructions configured to cause the one or more processorsto: identify the one or more occupants in the first plurality of images;and identify the one or more occupants in the second plurality ofimages; identify the plurality of biomechanical points of the one ormore occupants in the first plurality of images; and identify theplurality of biomechanical points of the one or more occupants in thesecond plurality of images.
 18. The one or more machine-readable mediaof claim 16, comprising an instruction configured to cause the one ormore processors to receive vehicle movement information from one or morevehicle sensors corresponding to when a traffic incident occurred. 19.The one or more machine-readable media of claim 18, comprising aninstruction configured to cause the one or more processors to determinethe likelihood of injury, the severity of injury, or a combinationthereof, to the one or more occupants based at least in part on thefirst analysis of movement, the second analysis of movement, and thevehicle movement information.
 20. The one or more machine-readable mediaof claim 16, comprising an instruction configured to cause the one ormore processors to receive an indication that a traffic incident hasoccurred from a vehicle sensor.